MIT researchers demonstrated that OpenAI's GPT-6 Astra can read and deliberately rewrite the weights of other AI models without traditional training. In one experiment, Astra boosted a Qwen model's math accuracy from 7.9% to 48.1% by changing only 0.016% of its weights. The approach could simplify AI optimization but still faces clear limitations.
This is a concrete, recent research breakthrough showing a novel capability of a frontier model, with quantitative results and clear implications for AI optimization.
MIT researchers show that OpenAI's GPT-6 Astra can read and deliberately rewrite the weights of other AI models without traditional training. In one experiment, Astra boosted a Qwen model's math accuracy from 7.9 to 48.1 percent by changing just 0.016 percent of its weights. The approach could fundamentally simplify AI optimization but still hits clear limits.
The article GPT-6 Astra sees the matrix and reprograms other AI models directly through their weights appeared first on The Decoder.
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